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Alistair Duke

Publications and source records attributed to Alistair Duke.

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Role-Based Agentic AI for Intent-Driven Network and Service Orchestration

Telecommunication networks are increasingly complex due to heterogeneous technologies, diverse service requirements, and growing demands for resource efficiency and business agility. Intent-Based Networking (IBN) and, more recently, agentic AI have emerged as promising paradigms to address this complexity through autonomous network management. However, existing approaches primarily focus on operational orchestration within Operations Support Systems (OSS) and lack an integrated framework that spans Business Support Systems (BSS) and OSS, limiting the realisation of true intent-to-business-to-network coordination. This paper presents a role-based multi-agent architecture (MAS) for end-to-end intent orchestration that mirrors Communication Service Provider (CSP) organisational structures. The proposed framework applies principles of functional decomposition, explicit task ownership, privacy-preserving domain separation, and domain-specific expertise within a hierarchical four-layer agent system spanning customer engagement, strategic planning, service delivery, and infrastructure provisioning. Leadership agents coordinate planning activities, whilst specialised service and resource agents are dynamically instantiated according to intent requirements. A proof-of-concept implementation demonstrates the feasibility of bridging the BSS-OSS divide through structured agent coordination, illustrating how agentic MAS can support accountable and scalable intent-driven service orchestration.

cs.NI

A Hypercat-enabled Semantic Internet of Things Data Hub: Technical Report

An increasing amount of information is generated from the rapidly increasing number of sensor networks and smart devices. A wide variety of sources generate and publish information in different formats, thus highlighting interoperability as one of the key prerequisites for the success of Internet of Things (IoT). The BT Hypercat Data Hub provides a focal point for the sharing and consumption of available datasets from a wide range of sources. In this work, we propose a semantic enrichment of the BT Hypercat Data Hub, using well-accepted Semantic Web standards and tools. We propose an ontology that captures the semantics of the imported data and present the BT SPARQL Endpoint by means of a mapping between SPARQL and SQL queries. Furthermore, federated SPARQL queries allow queries over multiple hub-based and external data sources. Finally, we provide two use cases in order to illustrate the advantages afforded by our semantic approach.

cs.AI